Image matching technologies have been widely applied in the fields of image retrieval, image splicing, target detection and recognition, robot scenario positioning and video contents analysis. Existing matching of images is generally based upon matching key pixels of the images, where it is determined that two images match when a key pixel of one image matches a key pixel of the other image. For example, for two images A and B to be matched, it is determined that the image A matches the image B when a key pixel of the image A has a corresponding matching key pixel in the image B, that is, a key pixel of the image A and a key pixel of the image B are a pair of matching pixels, where there is a consistent physical characteristic in the neighborhoods of the matching pixels.
Each key pixel of an image corresponds to two types of vectors, which are an eigenvector and a coordinate vector, where the eigenvector of the key pixel describes a physical characteristic in the neighborhood of the key pixel, and the coordinate vector of the key pixel describes the position of the key pixel. Thus currently a key pixel of one image has such a corresponding matching key pixel in the other image that is determined primarily based upon the eigenvectors of the key pixels. There are generally three existing methods of matching key pixels of two images based upon eigenvectors of the key pixels, which are a threshold matching method, a nearest neighbor threshold matching method and a nearest neighbor distance ratio matching method.
In the threshold matching method, for an eigenvector of a key pixel to be matched of a first image, an eigenvector, in a set of eigenvectors of a second image, at a distance, below a preset threshold, from the eigenvector of the key pixel to be matched is determined as a matching eigenvector, and the key pixel to be matched and a key pixel corresponding to the determined matching eigenvector are determined as a pair of matching pixels, where the preset threshold ranges from 0 to 1. With this threshold matching method, the matching pixels may be determined at low reliability due to a number of possible eigenvectors satisfying the condition of their distances from the eigenvector of the key pixel to be matched being below the preset threshold.
In the nearest neighbor threshold matching method, for an eigenvector of a key pixel to be matched of a first image, an eigenvector, in a set of eigenvectors of a second image, at the lowest distance from the eigenvector of the key pixel to be matched is determined as a candidate eigenvector, the candidate eigenvector is determined as a matching eigenvector when the distance between the candidate eigenvector and the eigenvector of the key pixel to be matched is below a preset threshold, and the key pixel to be matched and a key pixel corresponding to the determined matching eigenvector are determined as a pair of matching pixels, where the preset threshold ranges from 0 to 1. With the preset threshold, the candidate eigenvector satisfying the condition of the preset threshold is determined as a matching eigenvector, and the key pixel to be matched and a key pixel corresponding to the determined matching eigenvector are determined as a pair of matching pixels, but actually that the matching eigenvector satisfies the condition of the preset threshold is a necessary condition for correct matching of the key pixel to be matched with the key pixel corresponding to the matching eigenvector, so with the nearest neighbor threshold matching method, it has not been verified whether the key pixel to be matched and the key pixel corresponding to the matching eigenvector satisfy a sufficient condition for correct matching, and consequently the matching pixels may be determined at a high error ratio in the nearest neighbor threshold matching method.
In the nearest neighbor distance ratio matching method, for an eigenvector of a key pixel to be matched of a first image, a first eigenvector and a second eigenvector, in a set of eigenvectors of a second image, at the lowest and second lowest distances from the eigenvector of the key pixel to be matched are determined respectively; a first distance between the eigenvector of the key pixel to be matched and the first eigenvector is determined, and the second distance between the eigenvector of the key pixel to be matched and the second eigenvector is determined, and the key pixel to be matched and a key pixel corresponding to the first eigenvector are determined as a pair of matching pixels when the ratio of the first distance to the second distance is below a preset threshold, where the preset threshold ranges from 0 to 1. Similarly to the nearest neighbor threshold matching method, the matching pixels may be determined at a high error ratio in the nearest neighbor distance ratio matching method.
In summary, the matching pixels may be determined at low reliability and a high error ratio in the prior art where the key pixels of the two images are matched based upon the eigenvectors of the key pixels.